Probabilistic Dynamics : The Mathematical and Computing Problems Ahead

The methodology of probabilistic dynamics viewed as a continuous event tree theory is reviewed and other existing methods are shown to be particular cases corresponding to definite assumptions. Prospects for improvement of related numerical algorithms are examined.

[1]  B. Matkowsky,et al.  The Exit Problem for Randomly Perturbed Dynamical Systems , 1977 .

[2]  Elmer E Lewis,et al.  Component dependency models in Markov Monte Carlo simulation , 1985 .

[3]  Zeev Schuss,et al.  Theory and Applications of Stochastic Differential Equations , 1980 .

[4]  P. C. Cacciabue,et al.  Expanding the scope of DYLAM methodology to study the dynamic reliability of complex systems: the case of chemical and volume control in nuclear power plants , 1992 .

[5]  Jeffery D. Lewins,et al.  System reliability perturbation studies by a Monte Carlo method , 1991 .

[6]  D. Ingman,et al.  Dynamic character of failure state in damage accumulation processes , 1991 .

[7]  Carol-Sophie Smidts,et al.  Probabilistic reactor dynamics. II: A Monte Carlo study of a fast reactor transient , 1992 .

[8]  C. S. Hsu,et al.  Cell-to-Cell Mapping , 1987 .

[9]  H. Martz Bayesian reliability analysis , 1982 .

[10]  R. Righini,et al.  Analysis of non-Markovian systems by a Monte-Carlo method , 1991 .

[11]  Carol-Sophie Smidts Probabilistic reactor dynamics. IV. An example of man/machine interaction , 1992 .

[12]  Tunc Aldemir,et al.  Computer-Assisted Markov Failure Modeling of Process Control Systems , 1987, IEEE Transactions on Reliability.

[13]  Enrico Zio,et al.  Nonlinear Monte Carlo reliability analysis with biasing towards top event , 1993 .

[14]  J. Devooght,et al.  Probabilistic Reactor Dynamics —I: The Theory of Continuous Event Trees , 1992 .

[15]  Y.Smeers Core,et al.  Fiabilité des systèmes: Alain PAGES and Michel GONDRAN Volume 39 in: Collection de la Direction des Etutes et Recherches d'Electricité de France, Eyrolles, Paris, 1980, xxii + 323 pages, FF360.00 , 1982 .

[16]  William H. Press,et al.  Recursive stratified sampling for multidimensional Monte Carlo integration , 1990 .

[17]  Ioannis A. Papazoglou,et al.  Markovian reliability analysis under uncertainty with an application on the shutdown system of the Clinch River Breeder Reactor , 1980 .

[18]  T. D. Brown,et al.  Evaluation of severe accident risks: Quantification of major input parameters , 1992 .

[19]  Tunc Aldemir,et al.  A data base oriented dynamic methodology for the failure analysis of closed loop control systems in process plant , 1990 .

[20]  C. Gardiner Handbook of Stochastic Methods , 1983 .

[21]  N. Siu,et al.  Risk assessment for dynamic systems: An overview , 1994 .

[22]  A. Amendola Accident Sequence Dynamic Simulation Versus Event Trees , 1988 .

[23]  Elmer E Lewis,et al.  Monte Carlo reliability modeling by inhomogeneous Markov processes , 1986 .

[24]  A. Amendola,et al.  Event Sequences and Consequence Spectrum: A Methodology for Probabilistic Transient Analysis , 1981 .

[25]  G. Reina,et al.  DYLAM-1 : a software package for event sequence and consequence spectrum methodology , 1984 .

[26]  F. James,et al.  Monte Carlo theory and practice , 1980 .

[27]  I. Lux Monte Carlo Particle Transport Methods: Neutron and Photon Calculations , 1991 .

[28]  A. T. Bharucha-Reid Elements of the theory of Markov processes and their applications , 1961 .

[29]  Tunc Aldemir Quantifying setpoint drift effects in the failure analysis of process control systems , 1989 .

[30]  T. L. Chu,et al.  Time-dependent accident sequences including human actions , 1984 .

[31]  C. Smidts,et al.  Probabilistic reactor dynamics: Computational models , 1991 .

[32]  Carol-Sophie Smidts,et al.  Probabilistic reactor dynamics. III: A framework for time-dependent interaction between operator and reactor during a transient involving human error , 1992 .

[33]  Alessandro Birolini,et al.  On the Use of Stochastic Processes in Modeling Reliability Problems , 1985 .